Title of Talk: Detecting network anomalies and intrusions
Biography: Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, in 1974, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, in 1979 and 1981, respectively, and the Ph.D. degree in electrical engineering from University of California at Los Angeles, in 1986. She is currently a Professor in the School of Engineering Science at Simon Fraser University, Burnaby, British Columbia, Canada. From 1995 to 1997, she was a National Science Foundation (NSF) Visiting Professor in the Electrical Engineering and Computer Sciences Department, University of California, Berkeley. She was a Research Scientist at Bell Communications Research, Morristown, NJ, from 1990 to 1997, and a Member of the Technical Staff at AT&T Bell Laboratories, Murray Hill, NJ, from 1988 to 1990. Her research interests include high-performance communication networks, control of communication systems, computer-aided circuit analysis and design, and theory of nonlinear circuits and dynamical systems.
Dr. Trajkovic serves as IEEE Division X Delegate/Director (2019-2020) and served as IEEE Division X Delegate-Elect/Director-Elect (2018). She served as Senior Past President (2018-2019), Junior Past President (2016-2017), President (2014-2015), President-Elect (2013), Vice President Publications (2012-2013, 2010-2011), Vice President Long-Range Planning and Finance (2008-2009), and a Member at Large of the Board of Governors (2004-2006) of the IEEE Systems, Man, and Cybernetics Society. She served as 2007 President of the IEEE Circuits and Systems Society and a member of its Board of Governors (2004-2005, 2001-2003). She is Chair of the IEEE Circuits and Systems Society joint Chapter of the Vancouver/Victoria Sections. She was Chair of the IEEE Technical Committee on Nonlinear Circuits and Systems (1998). She is General Co-Chair of SMC 2020 and SMC 2020 Workshop on BMI Systems and served as General Co-Chair of SMC 2019 and SMC 2018 Workshops on BMI Systems, SMC 2016, and HPSR 2014, Special Sessions Co-Chair of SMC 2017, Technical Program Chair of SMC 2017 and SMC 2016 Workshops on BMI Systems, Technical Program Co-Chair of ISCAS 2005, and Technical Program Chair and Vice General Co-Chair of ISCAS 2004. She served as an Associate Editor of the IEEE Transactions on Circuits and Systems (Part I) (2004-2005, 1993-1995), the IEEE Transactions on Circuits and Systems (Part II) (2018, 2002-2003, 1999-2001), and the IEEE Circuits and Systems Magazine (2001-2003). She is a Distinguished Lecturer of the IEEE Systems, Man, and Cybernetics Society (2020-2021) and the IEEE Circuits and Systems Society (2010-2011, 2002-2003). She is a Professional Member of IEEE-HKN and a Life Fellow of the IEEE..
Abstract: The Internet, social networks, power grids, gene regulatory networks, neuronal systems, food webs, social systems, and networks emanating from augmented and virtual reality platforms are all examples of complex networks. Collection and analysis of data from these networks is essential for their understanding. Traffic traces collected from various deployed communication networks and the Internet have been used to characterize and model network traffic, analyze network topologies, and classify network anomalies. Data mining and statistical analysis of network data have been employed to determine traffic loads, analyze patterns of users' behavior, and predict future network traffic while spectral graph theory has been applied to analyze network topologies and capture historical trends in their development. Machine learning techniques have proved valuable for predicting anomalous traffic behavior and for classifying anomalies and intrusions in communication networks. Applications of these tools help understand the underlying mechanisms that affect behavior, performance, and security of computer networks.
Speaker: Dr. Juan Manuel Corchado, Director - European IoT Digital Innovation Hub, Director- BISITE Research Group, University of Salamanca & President of the Air Institute, Spain
Title of Talk: Efficient Deployment of DeepTech AI Models in Engineering Solutions
Biography: Juan Manuel Corchado (born May 15, 1971 in Salamanca, Spain). He is Full Professor with Chair at the University of Salamanca. He was Vice President for Research and Technology Transfer from December 2013 to December 2017 and the Director of the Science Park of the University of Salamanca, Director of the Doctoral School of the University until December 2017 and also, he has been elected twice as the Dean of the Faculty of Science at the University of Salamanca. In addition to a PhD in Computer Sciences from the University of Salamanca, he holds a PhD in Artificial Intelligence from the University of the West of Scotland. Juan Manuel Corchado is Visiting Professor at Osaka Institute of Technology since January 2015 and Visiting Professor at the Universiti Malaysia Kelantan.
Corchado is the Director of the European IoT Digital Innovation Hub and of the BISITE (Bioinformatics, Intelligent Systems and Educational Technology) Research Group, which he created in the year 2000, President of the AIR Institute, Academic Director of the Institute of Digital Art and Animation of the University of Salamanca and has been President of the IEEE Systems, Man and Cybernetics Spanish Chapter. He also oversees the Master´s programs in Digital Animation, Security, Blockchain, IoT, Mobile Technology, Information Systems Management and Agile Project Management at the University of Salamanca.
Corchado has supervised more than 25 PhD theses, is author of over 800 research peer review papers and books
, has chaired the scientific committee of more than 30 international conferences, and is also Editor-in-Chief of Specialized Journals like ADCAIJ (Advances in Distributed Computing and Artificial Intelligence Journal) and OJCST (Oriental Journal of Computer Science and Technology)..
Artificial Intelligence revived in the last decade. The need for progress, the growing processing capacity and the low cost of the Cloud have facilitated the development of new, powerful algorithms. The efficiency of these algorithms in Big Data processing, Deep Learning and Convolutional Networks is transforming the way we work and is opening new horizons. Thanks to them, we can now analyse data and obtain unimaginable solutions to today’s problems. Nevertheless, our success is not entirely based on algorithms, it also comes from our ability to follow our “gut” when choosing the best combination of algorithms for an intelligent artefact. It's about approaching engineering with a lot of knowledge and tact. This involves the use of both connectionist and symbolic systems, and of having a full understanding of the algorithms used. Moreover, to address today’s problems we must work with both historical and real-time data. We must fully comprehend the problem, its time evolution, as well as the relevance and implications of each piece of data, etc.It is also important to consider development time, costs and the ability to create systems that will interact with their environment, will connect with the objects that surround them and will manage the data they obtain in a reliable manner.
In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems.It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively."Smart" infrastructures need to incorporate all added-value resources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities. The use of edge platforms or fog computing helps increase efficiency, reduce network latency, improve security and bring intelligence to the edge of the network;close to the sensors, users and to the medium used.
This keynote will present success stories regarding biotechnology, smart cities, industry 4.0, the economy, and others. All these fields require the development of interactive, reliable and secure systems which we are capable of building thanks to current advances.Several use cases of intelligent systems will be presented and it will be the different processes have been optimized by means of tools that facilitate decision-making.
Speaker: Dr. Arpan Pal, Chief Scientist and Research Area Head, Embedded Systems and Robotics, TCS Research, India
Title of Talk: Device Edge Computing: Next Frontiers for IoT and Robotics
Biography: Arpan Pal received both his B.Tech and M.Tech from Indian Institute of Technology, Kharagpur, India in Electronics and Telecommunications and PhD. from Aalborg University Denmark. He has more than 27 years of experience in the area of Signal Processing, Communication, Embedded Systems and Robotics. Currently he is with Tata Consultancy Services (TCS), where, as Chief Scientist, he is heading the Embedded Systems and Robotics Research Area in TCS Research. Prior to joining TCS, Arpan has led the real-time Systems group in Macmet Interactive Technology Pvt. Ltd. and had been involved in design / development of missile seeker signal processors in Defense Research and Development Organization (DRDO), Govt. of India. His research interests include Sensing & IoT, Signal Processing & AI, Robotics & Edge Processing. He has contributed in research, development and deployment of embedded sensing and control systems products in areas of Telecommunication Systems, Missile Systems, Interactive Television, Internet of Things, Robotics and AI driven analytics. Arpan has more than 125 papers and book chapters till date in reputed Journals and Conferences. He has also authored a complete book on IoT. He has filed for more than 150 patents and has more than 100 patents granted to him in different geographies. He had been on the editorial board for reputed journals like ACM Transactions on Embedded Computing Systems, IEEE Transactions on Emerging Topics in Computing and Springer-Nature Journal on Computing Systems. He is a Senior Member of IEEE and is engaged in the innovation space in different industry bodies like NASSCOM, CII, BCCI and various start-up accelerators. He is on the review board of various Govt. initiatives like IMPRINT, CSIR Mission mode initiative etc.
Abstract: Edge computing is the next frontier for IoT where analytics and AI needs to be performed in the Edge device itself without sending the sensor data to the cloud. In this talk we will discuss the main drivers for device edge computing, outline the application use cases and provide a glimpse of the required technology – current and future.
Speaker: Dr. Danda B. Rawat, Howard University, Washington, DC, USA
Title of Talk: Secure and Trustworthy Machine Learning and Artificial Intelligence for Emerging Systems and Applications: The Triumph and Tribulation
Dr. Danda B. Rawat is a Full Professor in the Department of Electrical Engineering & Computer Science (EECS), Founder and Director of the Howard University Data Science and Cybersecurity Center, Director of Cyber-security and Wireless Networking Innovations (CWiNs) Research Lab, Graduate Program Director of Howard CS Graduate Programs and Director of Graduate Cybersecurity Certificate Program at Howard University, Washington, DC, USA. Dr. Rawat is engaged in research and teaching in the areas of cybersecurity, machine learning, big data analytics and wireless networking for emerging networked systems including cyber-physical systems, Internet-of-Things, multi domain battle, smart cities, software defined systems and vehicular networks. His professional career comprises more than 18 years in academia, government, and industry. He has secured over $16 million in research funding from the US National Science Foundation (NSF), US Department of Homeland Security (DHS), US National Security Agency (NSA), US Department of Energy, National Nuclear Security Administration (NNSA), DoD and DoD Research Labs, Industry (Microsoft, Intel, etc.) and private Foundations. Dr. Rawat is the recipient of NSF CAREER Award in 2016, Department of Homeland Security (DHS) Scientific Leadership Award in 2017, Researcher Exemplar Award 2019 and Graduate Faculty Exemplar Award 2019 from Howard University, the US Air Force Research Laboratory (AFRL) Summer Faculty Visiting Fellowship in 2017, Outstanding Research Faculty Award (Award for Excellence in Scholarly Activity) at GSU in 2015, the Best Paper Awards (IEEE CCNC, IEEE ICII, BWCA) and Outstanding PhD Researcher Award in 2009. He has delivered over 20 Keynotes and invited speeches at international conferences and workshops. Dr. Rawat has published over 200 scientific/technical articles and 10 books
. He has been serving as an Editor/Guest Editor for over 50 international journals including the Associate Editor of IEEE Transactions of Service Computing, Editor of IEEE Internet of Things Journal, Associate Editor of IEEE Transactions of Network Science and Engineering and Technical Editors of IEEE Network. He has been in Organizing Committees for several IEEE flagship conferences such as IEEE INFOCOM, IEEE CNS, IEEE ICC, IEEE GLOBECOM and so on. He served as a technical program committee (TPC) member for several international conferences including IEEE INFOCOM, IEEE GLOBECOM, IEEE CCNC, IEEE GreenCom, IEEE ICC, IEEE WCNC and IEEE VTC conferences. He served as a Vice Chair of the Executive Committee of the IEEE Savannah Section from 2013 to 2017. Dr. Rawat received the Ph.D. degree from Old Dominion University, Norfolk, Virginia. Dr. Rawat is a Senior Member of IEEE and ACM, a member of ASEE and AAAS, and a Fellow of the Institution of Engineering and Technology (IET).
Abstract: This keynote focuses on both AI for cybersecurity and cybersecurity for AI for emerging systems and applications. Lately, ML algorithms and AI systems have been shown to be able to create machine cognition comparable to or even better than human cognition for some applications. Machine learning algorithms are now regarded as very useful cybersecurity solutions for different emerging applications. However, because ML algorithms and AI systems can be controlled, dodged, biased, and misled through flawed learning models and input data, they need robust security features and trustworthy AI. It is very important to design and evaluate/test ML algorithms and AI systems that produce reliable, robust, trustworthy, explainable and fair/unbiased outcomes to make them acceptable by diverse users. The keynote covers applications and use cases of secure and trustworthy ML/AI and their success and pitfalls.
Speaker: Dr. Nicolas Sklavos, University of Patras, Hellas
Title of Talk: In Hardware We Trust: Electronic Design Automation
Dr. Nicolas Sklavos is Associate Professor, in Computer Engineering and Informatics Department (CEID), Polytechnic School, University of Patras, Hellas. He is Director of SCYTALE Group. His research interests include Cryptographic Engineering, Hardware Security, Cyber Security, Digital Systems Design, and Embedded Systems. He has participated to a number of European/National, Research and Development Projects. He has received several scientific awards in the related areas of his research. He has participated to the organization of international scientific conferences, of IEEE/ACM/IFIP, serving several committee duties, as well as Editorial Board Member of Scientific Journals. He has authored technical papers, books, chapters, reports etc, in the areas of his research. His published works has been cited in several papers of other authors, in technical literature. He is Senior Member of IEEE, Associated Member of HiPEAC and member of IACR. His works, have received a great number of references, in scientific, technical literature. (Homepage: http://www.scytale.ceid.upatras.gr
Abstract: Modern handheld devices and systems are developed day by day, in order to satisfy the complexity of users’ needs and applications. Nowadays, integrated circuits (ICs) play a sensitive role in devices’ operation, since they are the main cores for almost each type of process and data transaction. The needs for high performance, minimized area, and less power, are more demanding each time, and electronic design automation (EDA), is oriented as a crucial factor, for these targets. Although, besides the traditional circuits and systems, design approaches, the arising threats in hardware each time, make very important the priority for secure hardware design, and trusted devices, at the same time. Traditional approaches of design and test, are argued, since most of the processes’ parts, need considerations, assumptions and specifications, for both trustworthy and security in all metrics, including modeling and evaluation. This keynote talk, gives a detailed overview of hardware security and EDA approaches, including security threats, in integrated circuits, though the design cycle. It also, deals with, the countermeasures and the motivation of the prior art. Examples of modern applications are introduced, in sense of trusted hardware, and secure by design. Solutions, and alternative approaches are figured out, as well, detailed overview is discussed, for the expectations of future, for both users’ applications, and devices.
Speaker: Dr. El-Sayed El-Alfy, King Fahd University of Petroleum and Minerals, Saudi Arabia
Title of Talk: Learning from Class-Imbalanced Data: Challenges,Methods and Applications
Biography: El-Sayed M. El-Alfy, Professor King Fahd Univ. of Petroleum and Minerals (KFUPM). He has 25+ years of experience in industry and academia involving research, teaching, supervision, curriculum design, program assessment and quality assurance. He is an active researcher in machine learning and nature-inspired computing and applications to data science and cyber analytics, pattern recognition, multimedia forensics, and security systems. He published numerously in peer-reviewed int’l journals and conferences, edited a number of books, contributed to organization of many int’l conferences, served as guest editor for a number of special issues, and been in editorial board of a number of premium journals including IEEE/CAA Journal of AutomaticaSinica, IEEE Transactions on Neural Networks and Learning Systems, International Journal on Trust Management in Computing and Communications, and Journal of Emerging Technologies in Web Intelligence (JETWI). He co-founded and coordinated a research group on Intelligent Systems at KFUPM. He is a member of IEEE Computational Intelligence Society, and x-member of ACM and IEEE Computer Society. His work has been internationally recognized and received several awards.
Abstract: Nowadays, machine learning and intelligent systems are gaining increasing importance in this era of digital transformation.As more data is generated, the advances in this field present new opportunities in a wide spectrum of domains such as healthcare, finance, social media, cybersecurity, industrial systems, and sensor networks. However, some events or classes are rare and not equally represented in data for many real-world applications. This imposes several challenges for standard machine learning classification algorithms. Though several approaches have been proposed over the past decades, there are open issues that need further investigation. In this talk, we review majorresearch challenges and state-of-the-art solutions with examples for handling imbalanced datasets in order to build more effective models.
Speaker: Dr. Axel Sikora, University of Applied Sciences Offenburg, Germany
Title of Talk: AI Approaches for IoT Security Analysis
Biography: Axel Sikora holds a master (M.Sc. / Dipl.-Ing.) of Electrical Engineering and a master of Business Administration (MBA, Dipl. Wirt-Ing.), both from Aachen Technical University, Germany. He is a DAAD alumnus from 1990/91 in St Petersburg Politechnical Institute. He has done a Ph.D. (Dr.-Ing.) in Electrical Engineering at the Fraunhofer Institute of Microelectronics Circuits and Systems, Duisburg, with a thesis on SOI-technologies. After various positions in the telecommunications and semiconductor industry, he became a professor at the Baden-Wuerttemberg Cooperative State University Loerrach in 1999. In 2011, he joined Offenburg University of Applied Sciences, where he now leads the Institute of Reliable Embedded Systems and Communication Electronics (ivESK). Since Jan 2016, he is also deputy member of the board to Hahn-Schickard Association of Applied Research, one of the state-funded research institutes in Baden-Wuerttemberg, where he now leads two engineering divisions "Embedded Solutions" and "Software Solutions". Since October 2019, he is also affiliated professor to Technical Faculty of Freiburg University. His major interest is in the field of efficient, energy-aware, autonomous, secure and value-added algorithms and protocols for wired and wireless embedded communication with a strong focus on primary communication, gateway solutions, and data analytics for cyber-physical systems. Dr. Sikora is founder and shareholder of STACKFORCE GmbH, an independent and successul spin-off engineering company around IoT connectivity solutions. He is author, co-author, and editor and coeditor of several textbooks and more than 250 papers in the field of embedded design and wireless & wired networking. Amongst many other duties, he serves as Chairman of the annual embedded world Conference (Nuremberg), the world's largest event on the topic.
Abstract: IoT networks are increasingly used as entry points for cyber attacks, as often they offer low security levels, as they may allow the control of physical systems, and as they potentially also open the access to other IT networks and infrastructures. Existing Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) mostly concentrate on legacy IT networks. Nowadays, they come with a high degree of complexity and adaptivity, including the use of Artificial Intelligence (AI) and Machine Learning (ML). It is only recently, that these techniques are also applied to IoT networks. The keynote gives on overview of the state of the art of IoT network security and about AI-based approaches for the IoT security analysis.